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Discussion
According to the MoH,26 it is becoming increasingly evident that many developing countries, including Ghana, would struggle to meet all the global targets required to improve their health sector. As a result, a national e-health system, the LHIMS, was necessary for the health sector to improve service efficiency and function as the country’s EHR and a biosurveillance system.26 Findings from the study revealed that the LHIMS enhances service delivery efficiency. The health professionals who participated in the study indicated that using the LHIMS lessens a patient’s time spent at the unit and facilitated quick task execution, as well as assists in giving the patients the proper care. Admittedly, these results are consistent with the 2005 and 2010 National E-Health Strategy Policy’s objective27 and with the international standard, HealthIT.Gov28 which suggests that an EHR system should offer quick access to patient records and efficient job execution in addition to providing accurate, full and up-to-date patient information at the point of care. The findings show that the LHIMS has these features and is now deployed and used widely within the health sector of Ghana. However, results from Hodgson et al29 research reported inefficiencies of EHRs adoption such as system users being permanently connected to a computer and using multiclick diagnostic chart navigations which make the use of EHR systems by health professionals undesirable. However, the findings from our study indicated the contrary. The reasons that might account for the differences in literature may be due to several factors including, the type of EHR software deployed, the design of the system interface, personal factors such as age, sex, work experience, training prior to system use and type of profession.30 For instance, Shanafelt et al30 argue that several factors influence the efficient use of EHR systems. According to the technology acceptance model by Davis,21 external factors such as age, gender and organisational factors are theorised to influence the perceived usefulness (efficiency) of an EHR system. As a result, this current study hypothesised that health professional’s efficient use of the LHIMS is influenced by sociodemographic characteristics (age, sex, educational qualification and years of work experience), professional characteristics (staff category, place of training and institution of training) and computer self-efficacy. The results of the multivariate analysis for sociodemographic characteristics (age, sex, educational qualification and years of work experience) of health professionals and the efficient use of EHRs revealed that age, sex and educational qualification had an insignificant effect on the efficient use of EHR. However, years of work experience were the only sociodemographic characteristic that was found to have a statistically significant influence on the efficient use of LHIMS. The results agree with the findings from Adedeji et al,31 Khairat et al32 and Bae and Encinosa.33 Adedeji et al in their study found a significant association between the use of EHR and age, availability of computer systems, years of working experience and training of users.31 The results of their study are in contrast with that found in this study except in terms of years of work experience which was found to have no significant effect on efficiency in the use of EHR among health professionals.31 Khairat et al in their study examined how doctors’ performance, efficiency, perceived workload, happiness and usability of the EHR differed depending on their age, gender, professional function and years of experience with the EHR.32 They found some differences in efficiency among male and female physicians.32 The data showed that female physicians are more efficient in using EHRs as they used the EHR’s general search bar and filters, which resulted in a more efficient search, and this means that differences in sex among health professionals play a role in their efficient use of EHR.32 This finding contrasts with the one obtained in this study. However, even though sex, in general, was found to have no significant effect on the efficient use of EHR, the results, show that females in practice will be able to use the LHIMS-EHR more efficiently as compared with their male colleagues. This somewhat contrasting analysis may be due to the bivariate analysis which showed that the sex of health professionals has an association with their efficient use of EHR.
Bae and Encinosa33 in their study revealed that age and years of work experience matter in the efficient use of an EHR system.33 They found that older physicians who have more years of experience in the field were better at integrating EHR into clinical practice as compared with younger physicians with just a few years of work experience.33 Their study, therefore, provides support for the finding that years of work experience have played a major role in the efficient use of LHIMS by health professionals but contrasts with the finding that the age of health professionals does not affect how efficiently they use EHR. These findings indicate that not all external factors (age, sex and education) in the technology acceptance model by Davis21 may predict differences in the efficient use of the LHIMS and the variation in the literature is dependent on the type of EHR software adopted.
Aside from social demographic characteristics, the multivariate analysis of professional characteristics and efficient use of the LHIMS revealed an insignificant association between professional type and the institution where health professionals receive their training and efficient use of the LHIMS. However, the bivariate analysis of professional type and efficiency in the use of the LHIMS showed a significant association between the two. This means that the professional characteristics of health professionals do not affect how efficiently respondents used the LHIMS taking into consideration other variables such as age, sex, education and years of work experience. Similar findings are noted in the works of Nandikove et al.34 The researchers indicated no significant differences among professional types concerning the use of the EHR system in Kakamega County, Kenya.34
The multivariate analysis of training/computer efficacy showed that computer efficacy had a significant effect on the efficient use of LHIMS whereas training was found to have no significant effect. This means that health professionals cannot use the LHIMS efficiently without computer efficacy. However, whether they receive training on using EHR systems does not greatly enhance their efficiency. Contrarily, Butcher found different results on training and professional type.35 According to Butcher, health professionals who received training in EHR systems used relatively less time working in the EHR systems as compared with when they had not received any training.35
However, the bivariate analysis showed a significant relationship between the two even though the multivariate analysis revealed there is no causal relationship between the two. It can therefore be inferred that even though training does not significantly affect health professionals’ efficiency with LHIMS, it can go a long way to improve their proficiency in the use of the system. This may be because health professionals may not be able to use EHR systems most optimally as they may not have received any prior training on EHR systems in their training institutions. It may also be that the training was not effective since most respondents received just a day of training and some did not receive training at all but relied on their colleagues for support in using the LHIMS. Both situations necessitate training specific to the EHR system being used at their health facility for improved proficiency.
The results of the study pertaining to service delivery efficiency revealed that sociodemographic characteristics and the computer efficacy of health professionals are very important factors if they are to use the LHIMS efficiently. This implies that hospital governing bodies and health administrators will need to make sure that all health professionals that will be posted or hired have taken some general computing courses as, without it, efficient use of the LHIMS at the facility level will be significantly affected. Also, the MoH and its Agencies including hospital managers need to ensure that new entrant of health professionals with little or no work experience are to be trained and paired with experienced system users of the LHIMS. This is to ensure that the inefficiencies identified with the use of EHR systems by other researchers will not be experienced at the centre as they have serious repercussions for patients as well as the institution.
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